Healthcare is one of the sectors where an AI chatbot can bring enormous value – but also cause harm if deployed incorrectly. Patients ask about medications, symptoms, appointment availability, and reimbursements. Answers must be precise, current, and based solely on approved content.
Why traditional chatbots fail in healthcare
Most AI chatbots “hallucinate” – generating answers that sound credible but are false or out of date. In e-commerce a hallucination means a mistake in a product description. In healthcare – a potential patient safety risk.
Problems with typical medical chatbots:
– Give medication information without checking current product labelling
– Generalise symptoms and “diagnose” based on general knowledge
– Don’t respect legal disclaimers and warnings
– Don’t distinguish between information for patients and for physicians
AIGoChat’s approach: knowledge-base-first
AIGoChat works differently from typical chatbots. The bot answers solely from your knowledge base – it doesn’t draw on the AI model’s general medical knowledge. If the information isn’t in the base, the bot says: “I don’t have that information. Please contact our team on…”
This is a fundamental difference for medical applications.
What to index at a medical facility
Registration and organisation:
– Appointment hours for individual specialists
– How to book appointments (phone, online, through a patient portal)
– Documents required at first visit
– Telemedicine information
Services and specialisations:
– List of available specialisations and doctors
– Scope of diagnostic tests offered
– Preparation instructions (fasting, no creams, etc.)
– Results turnaround times
Financial information:
– Private service price list
– What is covered by insurance
– Accepted payment methods
– Private health insurance information
Key settings for a medical chatbot
1. Enable “knowledge-base only” mode – bot doesn’t use general AI knowledge
2. Configure fallback message: “I don’t have that information. For medical questions contact our staff at [tel] or through the contact form.”
3. Add disclaimer to welcome message: “I’m an information chatbot and do not provide medical advice. In emergencies call 911 or your local emergency number.”
4. Set automatic handoff to an agent on keywords: “pain”, “urgent”, “emergency”
Deployment example: MedCentre clinic
A clinic with 12 specialists deployed AIGoChat to relieve the reception desk. Results after 2 months:
– 1,200 conversations handled automatically per month
– Reception relieved of 65% of informational queries (hours, documents, prices)
– Zero instances of incorrect medical information given (bot referred patients to reception for questions outside the base)
– Patient satisfaction rating: 4.6/5
Regulatory compliance (GDPR, medical data protection)
AIGoChat does not process sensitive patient data (SSN, diagnosis, test results) within the chatbot. The bot collects only email and optionally a name – only if you enable that feature.
Infrastructure: EU servers (Frankfurt), TLS 1.3 encryption, option for automatic conversation history deletion after 30/90 days.
Important: An AI chatbot does not replace medical advice. Always configure a clear warning and a path to reach a human.